Systems and methods for fraud prevention based on video analytics

ABSTRACT

A video analytics based image verification system for obtaining initial vehicle profiles is presented. The system may include an external processing server that receives a location of a vehicle and proximate traffic information to determine whether it is safe for a user to obtain an initial vehicle profile. The external processing server may further determine first and second profile features from video data indicative of the vehicle. The external processing server may compare the second profile feature to an image verification indicator to generate an image verification score. A provider server may receive the first profile feature and the image verification score from the external processing server, and update a risk evaluation to include the initial vehicle profile if the image verification score is above an image verification threshold.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to video analytics based imageverification and, more particularly, to a system and method forobtaining an initial vehicle profile based on video data indicative of avehicle by comparing a profile feature included in the video data to animage verification indicator.

BACKGROUND

As a general principle of risk evaluation, high-fidelity data describingthe evaluated individual or item is of the utmost importance. Thanks toadvances in technology, specifically in the field of mobile technology,such high-fidelity data may be gathered locally by a mobile device user.However, the type of data that can be gathered is limited and vulnerableto modification, and local data gathering enables submissions that werenot traditionally possible.

Conventional techniques in risk evaluation through local data gatheringinvolve a user capturing still images of an item of interest forsubmission. Many conventional techniques utilize a mobile device'sintegrated camera to capture still images that are submitted through athird-party application to facilitate an interaction with thethird-party. However, such conventional techniques suffer from a varietyof potential submission issues, can place users in potentially dangeroussituations when capturing the still images, and result in low overallcustomer satisfaction levels through inefficient customer service basedon an evaluating entity's inability to accurately verify submissions.

Notably, and due to the relative simplicity associated with alteringstill images, many submissions feature altered or modified still images,or still images that represent another item entirely. Moreover, suchconventional techniques suffer from an inability to identify who issubmitting the still images because no in-person interaction takesplace, and thus permit submissions from unrelated persons accessing aregistered user's account and/or policy. Finally, such conventionaltechniques place users in exterior positions relative to the item ofinterest without any indication of external factors that might impacttheir efforts to capture the still images. All of these pitfallsassociated with conventional techniques erode customer confidence andnegatively impact an evaluating entity's ability to provide high levelsof customer service.

SUMMARY

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter.

In one embodiment, a video analytics based image verification system forobtaining initial vehicle profiles may be provided. The video analyticsbased image verification system may include an external processingserver configured to receive a geographic location of a vehicle andproximate traffic information; determine a profile safety index based onthe geographic location and the proximate traffic information; transmita notification for display on a mobile device indicating whether it issafe for a user to obtain an initial vehicle profile associated with arisk evaluation; receive video data indicative of the vehicle from themobile device; analyze the video data to identify a plurality of profilefeatures; determine a first profile feature from the plurality ofprofile features, wherein the first profile feature is related to thevehicle; determine a second profile feature from the plurality ofprofile features, wherein the second profile feature is related to animage verification indicator; determine a comparison of the secondprofile feature to the image verification indicator; and generate animage verification score based on the comparison of the second profilefeature to the image verification indicator. The video analytics basedimage verification system may further include a provider serverconfigured to receive the first profile feature and the imageverification score from the external processing server; and update therisk evaluation to include the initial vehicle profile based on thefirst profile feature indicating the image verification score relativeto an image verification threshold.

In another embodiment, a video analytics based image verification methodfor obtaining initial vehicle profiles may be provided. The videoanalytics based image verification method may include receiving, by anexternal processing server, a geographic location of a vehicle andproximate traffic information; determining, by the external processingserver, a profile safety index based on the geographic location and theproximate traffic information; transmitting, by the external processingserver, a notification for display on a mobile device indicating whetherit is safe for a user to obtain an initial vehicle profile associatedwith a risk evaluation; capturing, by the mobile device, video dataindicative of the vehicle; analyzing, by the external processing server,the video data to identify a plurality of profile features; determining,by the external processing server, a first profile feature from theplurality of profile features, wherein the first profile feature isrelated to the vehicle; determining, by the external processing server,a second profile feature from the plurality of profile features, whereinthe second profile feature is related to an image verificationindicator; determining, by the external processing server, a comparisonof the second profile feature to the image verification indicator;generating, by the external processing server, an image verificationscore based on the comparison of the second profile feature to the imageverification indicator; and updating, by a provider server, the riskevaluation to include the initial vehicle profile based on the firstprofile feature indicating the image verification score relative to animage verification threshold.

In yet another embodiment, a computer readable storage medium comprisingnon-transitory computer readable instructions stored thereon forobtaining initial vehicle profiles with image verification analytics maybe provided. The instructions, when executed on one or more processors,may cause the one or more processors to receive a geographic location ofa vehicle and proximate traffic information; determine a profile safetyindex based on the geographic location and the proximate trafficinformation; transmit a notification for display on a mobile deviceindicating whether it is safe for a user to obtain an initial vehicleprofile associated with a risk evaluation; receive video data indicativeof the vehicle; analyze the video data to identify a plurality ofprofile features; determine a first profile feature from the pluralityof profile features, wherein the first profile feature is related to thevehicle; determine a second profile feature from the plurality ofprofile features, wherein the second profile feature is related to animage verification indicator; determine a comparison of the secondprofile feature to the image verification indicator; generate an imageverification score based on the comparison of the second profile featureto the image verification indicator; and update the risk evaluation toinclude the initial vehicle profile based on the first profile featureindicating the image verification score relative to an imageverification threshold.

BRIEF DESCRIPTION OF THE DRAWINGS

The figures described below depict various aspects of the system andmethods disclosed herein. It should be understood that each figuredepicts an embodiment of a particular aspect of the disclosed system andmethods, and that each of the figures is intended to accord with apossible embodiment thereof. Further, wherever possible, the followingdescription refers to the reference numerals included in the followingfigures, in which features depicted in multiple figures are designatedwith consistent reference numerals.

FIG. 1 illustrates an example system for obtaining an initial vehicleprofile with image verification analytics;

FIG. 2 illustrates another example system for obtaining an initialvehicle profile with image verification analytics;

FIGS. 3A-3R depict a first set of example GUIs for an operationalembodiment of, for example, the system of FIG. 2;

FIGS. 4A-J depict a second set of example GUIs for an operationalembodiment of, for example, the system of FIG. 2;

FIG. 5 is a flowchart depicting an example method corresponding tovarious embodiments of the present disclosure.

The figures depict various aspects of the present invention for purposesof illustration only. One skilled in the art will readily recognize fromthe following discussion that alternative embodiments of the structuresand methods illustrated herein may be employed without departing fromthe principles of the invention described herein.

DETAILED DESCRIPTION

Although the following text sets forth a detailed description ofnumerous different embodiments, it should be understood that the legalscope of the description is defined by the words of the claims set forthat the end of this patent and equivalents. The detailed description isto be construed as exemplary only and does not describe every possibleembodiment since describing every possible embodiment would beimpractical. Numerous alternative embodiments could be implemented,using either current technology or technology developed after the filingdate of this patent, which would still fall within the scope of theclaims.

It should also be understood that, unless a term is expressly defined inthis patent using the sentence “As used herein, the term ‘_’ is herebydefined to mean . . . ” or a similar sentence, there is no intent tolimit the meaning of that term, either expressly or by implication,beyond its plain or ordinary meaning, and such term should not beinterpreted to be limited in scope based on any statement made in anysection of this patent (other than the language of the claims). To theextent that any term recited in the claims at the end of this patent isreferred to in this patent in a manner consistent with a single meaning,that is done for sake of clarity only so as to not confuse the reader,and it is not intended that such claim term be limited, by implicationor otherwise, to that single meaning.

I. Example Systems and Related Functionality for Obtaining an InitialVehicle Profile with Image Verification Analytics

FIG. 1 illustrates an example system 100 for obtaining an initialvehicle profile with image verification analytics. The example system100 may include a vehicle 102, a user electronic device 104, an providerserver 106, an external processing server 108, external databases 110,and a network 112. While illustrated in FIG. 1 as a single externaldatabase, in some embodiments the external databases 110 includes two ormore external databases. The network 110 may be a computer network of aninsurance provider (e.g., provided or used by the insurance provider orcommunications over which the insurance provider otherwise controls orfacilitates).

In reference to the example system 200 of FIG. 2, the user electronicdevice 104 may include a processor 202, a memory 204, a transceiver 206,and an imaging apparatus 208. While referred to herein as a “processor”and a “memory,” in some embodiments the processor 202 includes two ormore processors and the memory 204 includes two or more memories. Theprocessor 202 may be configured to process both still image data andvideo data (e.g., video data captured by user electronic device 104) andanalyze aspects of the still image data and/or video data. The memory204 may store computer-executable instructions, which may be executed bythe processor 202.

The imaging apparatus 208 may include, for example, a camera and/or avideo camera. As such, the imaging apparatus 208 may be configured tocapture one or both of still images and video footage. However, itshould be understood that the imaging apparatus 208 is not limited tothe cameras disclosed herein. Additionally, the user electronic device104 may be configured to receive communications from the provider server106 and/or the external processing server 108 in response totransmitting captured data and/or before, during, or after obtaining aninitial vehicle profile.

In various embodiments, the user electronic device 104 may executecomputer-executable instructions, such as a mobile application, thatallow the actions described herein to be implemented. For example, ifthe user electronic device 104 is a smartphone, the user may capturedata with the imaging apparatus 208 to transmit through the network 112to the provider server 106 and/or the external processing server 108 forprocessing. The user electronic device 104, and each of the computingdevices referred to herein, may be any suitable computing device suchas, but not limited to, a desktop computer, a laptop computer, a mobilephone such as a smart phone, a tablet, a phablet, smart glasses, otherwearable computing device(s), etc.

The provider server 106 may include a database 210, a processor 212, amemory 214, and a transceiver 216. While referred to herein as a“processor” and a “memory,” in some embodiments the processor 212includes two or more processors and the memory 214 includes two or morememories. The processor 212 may be configured to process both stillimage data and video data (e.g., video data captured by user electronicdevice 104) and analyze aspects of the still image data and/or videodata. The memory 214 may store computer-executable instructions, whichmay be executed by the processor 212. The database 210 may include aplurality of risk evaluations. The plurality of risk evaluations maycorrespond to a plurality of insured user profiles/accounts, insurancepolicies, or other user profiles, accounts, policies, etc.

Further, the plurality of risk evaluations may include relevant dataassociated with a user or item indicated in the risk evaluation. Forexample, if one of the plurality of risk evaluations is an insurancepolicy listing a first user as the insured, the insurance policy maylist the first user's name, age, gender, etc. Moreover, and as discussedfurther herein, the relevant data may include multiple profile featuresassociated with each risk evaluation. These profile features may, forexample, facilitate image verification by allowing the provider server106 to authenticate any attempts to access and/or modify detailsassociated with the corresponding risk evaluation. Correspondingly, theprovider, via the provider server 106, may more accurately andefficiently verify and pay claims, resulting in more satisfiedcustomers.

The external processing server 108 may include a database 218, aprocessor 220, a memory 222, and a transceiver 224. While referred toherein as a “processor” and a “memory,” in some embodiments theprocessor 220 includes two or more processors and the memory 222includes two or more memories. The processor 220 may be configured toprocess both still image data and video data (e.g., video data capturedby user electronic device 104) and analyze aspects of the still imagedata and/or video data. The memory 222 may store computer-executableinstructions, which may be executed by the processor 220.

The external processing server 108 may be connected to both the userelectronic device 104 and the provider server 106 via the network 112,such that each device (104, 106, and 108) may communicate to every otherdevice via their respective transceivers (206, 216, 224). For example,the external processing server 108 may receive profile features from theprovider server 106. The external processing server 108 may store thesereceived profile features in the database 218 and/or the memory 222.Thus, and as discussed further herein, either the provider server 106 orthe external processing server 108 may be configured to process,analyze, or otherwise interpret data captured by the user electronicdevice 104.

In embodiments where, as noted above and as further discussed below,video image data is provided to an insurance provider, the insuranceprovider may receive this indication at the provider server 106. Theprovider server 106, in embodiments, may also make available fordownload (e.g., via the network 112) the application executed by theuser electronic device 104 to implement functionality described herein.It will be appreciated that one or both of the provider server 106 orthe external processing server 108 may be a server provided by or usedby the insurance provider, or use of which the insurance providerotherwise controls or facilitates.

In embodiments, the network 112 may be or may include a network such asthe Internet and/or any other type of suitable network (e.g., a localarea network (LAN), a metropolitan area network (MAN), a wide areanetwork (WAN), a mobile network, a wired or wireless network, a privatenetwork, a virtual private network, etc.). The network 112 may also oralternatively be or include one or more cellular networks such as codedivision multiple access (CDMA) network, GSM (Global System for MobileCommunications) network, WiMAX (Worldwide Interoperability for MicrowaveAccess) network, Long Term Evolution (LTE) network, etc.

As further described below, the example systems (100, 200) facilitateobtaining an initial vehicle profile with image verification analytics,and allow, among other advantages, secure vehicle identification throughthe use of video image data, and a robust image verification analysisthrough profile features captured within the video image data. Videoimage data is more difficult to manipulate and/or alter than still imagedata. Thus, a submitted initial vehicle profile that contains videoimage data is more reliable based on the secure characteristics of thevideo image data. Simultaneously, profile features incorporated in thevideo image data benefit from the same difficulty to falsify, and add alayer of integrity to the submitted initial vehicle profile.Specifically, the incorporated profile features provide a form ofobjective data the system (e.g., 100, 200) may verify against known,authenticating information to ensure the submitted initial vehicleprofile originated from a known source. Such profile features featuringauthenticating information may satisfy state regulations requiring, forexample, initial vehicle inspections prior to the issuance of vehicleinsurance and/or claims processing. In any event, the authenticationfeatures of the example systems (100, 200) facilitate an evaluatingentity (e.g., insurance company, mechanic, medical underwriter)verifying and/or paying claims more accurately and efficiently,resulting in a higher level of overall customer service andsatisfaction. This increased efficiency and accuracy can yield furtherbenefits to customers in the form of risk evaluation benefits/incentives(e.g., lower insurance rates, premiums, deductibles, overall cost,etc.), which further increases customer satisfaction.

II. Example Operational Embodiments of the Systems

FIGS. 3A-R and 4A-J depict example interfaces associated with thesystems and methods. In embodiments, the interfaces may be displayed bya computing device in a user interface, such as the user electronicdevice 104 as discussed with respect to FIGS. 1 and 2. Additionally, theinterfaces may be accessed and reviewed by a user of an application orplatform, where the user may make selections, submit entries ormodifications, or facilitate other functionalities.

FIG. 3A depicts an interface 300 associated with the systems and methoddescribed herein. In particular, the interface 300 depicts an examplenotification a user may receive when initially attempting to participatein a risk evaluation procedure by obtaining an initial vehicle profile.For example, a user may initiate contact with an evaluating entity(e.g., an insurance provider, a mechanic, etc.) and said entity mayprovide the notification depicted in the interface 300.

In embodiments, the evaluating entity may use the notification to verifya set of contact information associated with the user. For example theuser may verify their contact information, and prompt the evaluatingentity to enable the user to obtain an initial vehicle profile. Theuser's verification may be transmitted from the user's device (e.g.,user electronic device 104) to the evaluating entity's device (e.g.,provider server 106) for further processing. Once processed, and asdepicted in FIG. 3B, the evaluating entity's device may send the user aresponsive notification (depicted in interface 301) confirming theuser's verification. Additionally, the system (100, 200) may requestthat the user obtain the initial vehicle profile at this point, or atany other suitable time.

In embodiments, a user may have an established vehicle account with anevaluating entity. For example, the evaluating entity's server (e.g.,provider server 106) may contain information relating to the user'svehicle in the evaluating entity's database (e.g., database 210). Inthis circumstance, it is possible that a user may not have obtained aninitial vehicle profile to incorporate into their vehicle account. Thus,and as illustrated in FIG. 3C, if a user logs into their vehicleaccount, the provider server 106 may provide an interface similar tointerface 302 for the user to inspect. The interface 302 may include anidentification area 303 that may include information such as policynumber, account status, vehicle picture, etc. Additionally, theinterface 302 may feature other relevant account information such asprojected bill amounts, bill due dates, and various options for the userto select. However, if the user has not obtained an initial vehicleprofile, the identification area 303 will not include a vehicle photo.

Thus, as depicted in the interface 304 of FIG. 3D, the evaluatingentity's server 106 may transmit a profile picture notification 305 fordisplay on the interface 304. The user may select the profile picturenotification 305 to initiate and/or enable several of thefunctionalities described herein. Selecting the profile picturenotification 305 may transition the user to interface 306, depicted inFIG. 3E. The interface 306 may enable a user to view all vehiclesincluded in a particular risk evaluation procedure (e.g., an insurancepolicy, a mechanic service history, etc.).

For example, the interface 306 may display all car insurance policiesassociated with a particular user profile. The interface 306 may includean individual vehicle profile 307 for each covered vehicle. Theindividual vehicle profile 307 may contain information indicating theinsurance policy number, the vehicle year, make, model, color, VIN, anda vehicle photo. If a user has not obtained an initial vehicle profile,the vehicle photo field of the individual vehicle profile 307 will beleft empty. Thus, if a user selects the individual vehicle profile 307depicted in FIG. 3E, the instructions executed on the processor (e.g.,processor 202) may transition the application from interface 306 tointerface 308, depicted in FIG. 3F.

The interface 308 includes an expanded individual vehicle profile 309and a photo capture selection area 310. The expanded individual vehicleprofile 309 may include similar information as the individual vehicleprofile 307, and may include additional information associated with thevehicle and/or the corresponding vehicle policy (or, for example, amaintenance history). For example, the expanded individual vehicleprofile 309 may include a policy issuance date, a policy term, a vehicleregistration state, current inspection records for the vehicle, etc.

The photo capture selection area 310 may be a user-selectable optionenabling certain features of the embodiments described herein. Forexample, a user may select the photo capture selection area 310, and theuser's device (e.g., user electronic device 104) may transition fromdisplaying interface 308 to displaying interface 311, as depicted inFIG. 3G. At this point, and as discussed further herein, the user'sdevice 104 may analyze the user's current geotagged location andproximate traffic information to determine whether it is safe for theuser to obtain the initial vehicle profile.

Once the user's device 104 determines that an initial vehicle profilecan be safely obtained, the device 104 may display interface 311. Theinterface 311 may represent a field of view (FOV) of a camera (e.g.,imaging apparatus 208). In other words, once a user selects the photocapture selection area 310, the user's device 104 may access the imagingapparatus 208 in order to capture images associated with a vehicleindicated in the expanded individual vehicle profile 309. The interface311 may also include a user identification area 312 featuring an imageor other representation of the user. The user identification area 312may capture an image of the user that the system (e.g., externalprocessing server 108) may use to positively verify the user's identityupon submission of the captured images.

To obtain an initial vehicle profile, the user may be required to obtainimages featuring various perspectives of the vehicle. Thus, as depictedin interface 313 of FIG. 3H, the system (100, 200) may require the userto capture an image of the front of a vehicle. Similarly, as depicted inFIGS. 3I-3P, the system (100, 200) may require the user to obtain imagesfeaturing the driver side (interface 314), driver side front (interface315), driver side rear (interface 316), front (interface 317), passengerside front (interface 318), passenger side (interface 319), passengerside rear (interface 320), and/or rear (interface 321) of the vehicle.It should be understood that the system (100, 200) may require anycapturing combination of these images in any order to obtain an initialvehicle profile.

Moreover, it is to be understood that the “images” referenced anddepicted in FIGS. 3H-3P may be extracted by the system (100, 200) from asingle, continuous stream of video data. To illustrate, the system (100,200) may prompt a user to capture the images referenced in FIGS. 3H-3Pby accessing and activating the video camera (e.g., imaging apparatus208) of the user's device (e.g., user electronic device 104). The userwould then conduct the vehicle walkaround by taking a continuous videoof the vehicle from various perspectives (e.g., as represented byinterfaces 313-321). Additionally, and as described further herein, thesystem (100, 200) may require the user to provide an identifying imageat some point during the vehicle walkaround to authenticate the videodata. Thus, after the user has completed the vehicle walkaround andwhile the video camera 208 remains activated, the user may take videoimages of their face or other identifying features, as displayed in theuser identification area 312.

Consequently, while obtaining these various images, a user may placethemselves in hazardous exterior conditions. For example, a user mayattempt to conduct the vehicle walkaround while on the side of a busyhighway, while their vehicle is parked on a busy residential street, orwhen weather conditions are potentially dangerous (e.g., during athunderstorm). As mentioned above, and as further discussed herein, thesystem (100, 200) may notify a user whether the current situation issufficiently safe to conduct the vehicle walkaround using situationaldata (e.g., location, traffic, weather, etc.) to generate a profilesafety index. In embodiments, the profile safety index is compared to aprofile safety index threshold indicative of the minimum allowablesafety index for the user to obtain the initial vehicle profile.

Once the system (100, 200) determines that the images acquired aresufficient, the user's device 104 may transition to interface 322, asdepicted in FIG. 3Q. The interface 322 may have a profile photo displayarea 323 and a profile photo selection area 324. The system (100, 200)may automatically determine which image of the various images capturesduring the vehicle walkaround is placed in the profile photo displayarea 323 to be edited by the user, or the user may select a preferredimage from the various images captured to serve as the basis for thevehicle's profile photo. The profile photo selection area 324 indicatesthe portion of the selected photo displayed in the profile photo displayarea 323 that will be displayed as the vehicle's profile photo. Forexample, and as depicted in FIG. 3R, the portion of the image indicatedby the profile photo selection area 324 is displayed in the interface325 under the vehicle's profile page.

FIG. 4A depicts an interface 400 associated with the systems and methoddescribed herein. In particular, the interface 400 depicts an exampleactive claims page an application may present to a user in response to auser's selection. The interface 400 includes an open claims area 401,which may indicate all of the user's open claims related to one vehicleor multiple vehicles. The user may interact with the open claims area401 by selecting a particular claim, and the user's device maytransition from interface 400 to the interface 402, as depicted in FIG.4B.

The interface 402 may include a claim documents submission area 403. Theclaim documents submission area 403 may indicate that a user mayoptionally upload documents via the application to assist in processingthe claim. The user may interact with the claim documents request area403 to prompt the application to transition from interface 402 tointerface 404, as depicted in FIG. 4C.

The interface 404 includes a requested claim documents area 405. Therequested claim documents area 405 may include a plurality of selectableoptions for a user. Each selectable option may indicate a specific typeof claim information the system (100, 200) may require to adequatelyprocess a claim. For example, the requested claim documents area 405 mayinclude selectable options for a user to enter photos of the accidentscene, a police report documenting events of an event, medical recordscorresponding to resulting medical treatment from an event, witnessstatements of an event, etc. In any event, once submitted, one or bothof the provider server 106 and/or the external processing server 108will store the submitted claim documents into the database (210, 218)for potential use in the method described further herein.

Additionally or alternatively, and as depicted in FIG. 4D, theapplication may present the interface 406 featuring a claim documentsrequest area 407 to a user when the system (100, 200) receives an updateto a user's claim. For example, when the user first submits a claim, thesystem (100, 200) may recognize that no claim documents are currentlyaccessible in the claims database (e.g., database 210, 218), or simplythat no current/updated claim forms are listed in the database (210,218) for the recently opened claim. In response, one or both of theprovider server 106 and/or the external processing server 108 may, viathe network 112, transmit a notification to the user electronic device104 to display the claim documents request area 407. In response to auser interacting with the claim documents request area 407, theapplication may transition to an interface similar to, for example,interface 404 to facilitate the user submitting relevant claimdocuments.

As an example of submitting claim documents, if a user selects an optionto provide images of the claim event, the application may transition tointerface 408, as depicted in FIG. 4E. Interface 408 includes an imagegallery featuring a vehicle image 409 and a user image 410. As furtherdiscussed herein, both the vehicle image 409 and the user image 410 maybe required by the system (100, 200) to process a claim. The vehicleimage 409 may indicate potential damage to the vehicle, and the userimage 410 may facilitate an authentication procedure to validate thesource of the claim.

Additionally or alternatively, the application may transition tointerface 411, as depicted in FIG. 4F. Interface 411 includes a filegallery featuring a set of vehicle claim images 412. Similar tointerface 408, the system (100, 200) may use images selected frominterface 411, and specifically from the vehicle claim images 412 tofacilitate processing a claim, in accordance with various embodimentsdescribed herein.

Additionally or alternatively, the application may transition tointerface 413, as depicted in FIG. 4G. Interface 413 may represent afield of view (FOV) of a camera (e.g., imaging apparatus 208). In otherwords, once a user interacts with the requested claim documents area 405or the claim documents request area 407, the user's device 104 mayaccess the imaging apparatus 208 in order to capture images associatedwith a claim. Similar to interfaces 408 and 411, the system (100, 200)may use images captured by the imaging apparatus 208 as displayed oninterface 413 to facilitate processing a claim, in accordance withvarious embodiments described herein.

Once selected and/or captured, the images may be displayed in theinterface 414, as depicted in FIG. 4H. The interface 414 includes theclaim documents request area 403 from interface 402, and additionallyfeatures the selected and/or captured image(s) described with referenceto FIGS. 4E-4G. Moreover, prior to submission, the application may offerthe user an opportunity to caption, comment, or otherwise label thesubmitted claim documents, as shown in interface 415 of FIG. 4I. Theinterface 415 includes a comment area 416 a user may use to describe theuploaded claim document.

For example, and as described further herein, the system (100, 200) mayuse the information the user submits in the comment area 416 to processa claim. More specifically, the system (100, 200) may use theinformation submitted in the comment area 416 to validate a submittedclaim document by, for example, requesting a signature corresponding toa known user. In embodiments, the comment area 416 may serve as apassword entry area. To illustrate, the system (100, 200) mayauthenticate claim submissions through authentication credentials in theform of a registered password associated with an account/user. Thus,once a user enters a claim document to facilitate the system (100, 200)processing a claim, the system (100, 200) may prompt a user to enter thepassword associated with the account to authenticate the attempted claimdocument entry.

After the system (100, 200) receives a claim document, the applicationmay transition from interface 415 to interface 417, as depicted in FIG.4J. The interface 417 includes a submitted claim document area 418, andan additional claim document area 419. The submitted claim document area418 may feature all validly submitted claim documents for a given claim.The submitted claim document area 418 may also include selectableoptions corresponding to each validly submitted claim document, such asoptions to comment (e.g., comment area 416) and/or remove the validlysubmitted claim document from the claim such that the system (100, 200)will not consider the document when processing the claim. The additionalclaim document area 419 may include a selectable option for a user toupload additional claim documents related to the claim event.

It should be understood that the functional embodiments of the system(100, 200) described herein may be applicable to both obtaining aninitial vehicle profile and obtaining a vehicle profile following aclaim event. Further, it should be understood that the “images” or“photos” described in reference to the functional embodiments of thesystem (100, 200) may be real-time streaming, or pre-recorded videoimage data to facilitate one or both of obtaining the initial vehicleprofile or obtaining the vehicle profile following a claim event.

III. Example of a Method for Obtaining an Initial Vehicle Profile withImage Verification Analytics

FIG. 5 is a flowchart depicting an example method 500 corresponding tovarious embodiments of the present disclosure. The method 500 begins atblock 502 where an external processing server (e.g., external processingserver 108) receives a geographic location of a vehicle (e.g., vehicle102) and proximate traffic information. In embodiments, the geographiclocation of the vehicle is a real-time indication of a location of thevehicle. For example, the external processing server 108 may receiveglobal-positioning system (GPS) data indicative of a real-timegeographical location of the vehicle. The GPS data may be received froma GPS module located in the vehicle 102, or from any other suitablelocation.

In embodiments, the proximate traffic information is indicative of oneor more of (i) an amount of expected traffic proximate to the vehiclebased on the geographic location of the vehicle or (ii) an amount ofactual traffic proximate to the vehicle based on the geographic locationof the vehicle. For example, the external processing server 108 mayreceive an amount of expected traffic proximate to the vehicle 102indicating the normal/historical traffic patterns for the geographiclocation. The expected traffic proximate to the vehicle 102 may includetimestamps to account for the fluctuations in traffic at a locationduring the course of a day, week, month, year, etc.; and the externalprocessing server 108 may receive the expected traffic proximate to thevehicle from an external database (e.g., external databases 110), orfrom an internal expected traffic list maintained at the provider server106.

The external processing server 108 may receive the amount of actualtraffic proximate to the vehicle 102 indicating an amount of real-timetraffic proximate to the vehicle 102. The external processing server 108may additionally determine an amount of actual traffic proximate to thevehicle 102 to utilize in proceeding steps of the method 500 based ontheir chronological distance from the current time. For example, if theexternal processing server 108 receives an indication that the trafficproximate to the vehicle 102 was heavier than normal in the preceding 30minutes, but has since dissipated to normal levels, the externalprocessing server 108 may discount the heavier than normal trafficindication in the proceeding steps of the method 500 as no longerrelevant, and thus not include the heavier than normal trafficindication in the actual traffic proximate to the vehicle 102. Moreover,the actual traffic proximate to the vehicle 102 will include timestampsto indicate the current time, and may include seconds, minutes, hours,and a day, week, month, year, etc. The external processing server 108may receive the actual traffic proximate to the vehicle from an externaldatabase (e.g., external databases 110), or from an internal actualtraffic list maintained and actively updated at the provider server 106.

The method 500 continues at block 504 by determining a profile safetyindex based on the geographic location and the proximate trafficinformation. The profile safety index may be an alphanumerical score orother suitable indication. Block 504 may be performed by, for example,the external processing server 108.

By including the geographic location, the profile safety index mayinclude the inherent geographic complications that a user may face whileattempting to obtain the initial vehicle profile. For example, in amountainous region, the user may be more likely to encounter unevenroad/parking surfaces that may lead to trips, falls, or otherpotentially injurious events. Similarly, the mountainous region may beprone to landslides, falling rocks, or other hazardous conditions thatare not conducive to obtaining an initial vehicle profile (e.g., walkingaround the exterior of the vehicle 102). As discussed further herein,the geographic information may also include weather informationindicative of historic weather patterns for the particular geographiclocation. Should the particular geographic location have a highpropensity for thunderstorms, tornadoes, blizzards, or other hazardousenvironmental conditions, then the safety profile index may decrease forthat particular geographic location.

Correspondingly, by including the proximate traffic information, theprofile safety index may include the inherent traffic hazards that auser may face while attempting to obtain the initial vehicle profile.For example, for an interstate highway, the proximate trafficinformation may indicate a high volume of traffic traveling at highspeeds. Accordingly, the profile safety index may decrease for thatlocation to indicate the unsafe conditions such a roadway poses to auser attempting to obtain an initial vehicle profile. As anotherexample, for a residential street, the proximate traffic information mayindicate a medium volume of traffic traveling at medium speeds.Accordingly, the profile safety index may slightly decrease for thatlocation to indicate the relatively unsafe conditions such a roadwayposes to a user attempting to obtain an initial vehicle profile. As yetanother example, for a user's driveway, the proximate trafficinformation may indicate a low volume of traffic traveling at lowspeeds. Accordingly, the profile safety index may increase for thatlocation to indicate the relatively safe conditions such a roadway posesto a user attempting to obtain an initial vehicle profile.

In embodiments, determining the safety profile index is further based onat least one of (i) a time of day, (ii) a current weather condition atthe geographic location, (iii) an expected weather condition at thegeographic location, (iv) a historical weather pattern at the geographiclocation, (v) a make of the vehicle, or (vi) a model of the vehicle. Forexample, the external processing server 108 may receive this additionalinformation included in the safety profile index from a weather serverand/or database (e.g., external databases 110), and may receive the makeand model of the vehicle from the provider server 106. The make andmodel of the vehicle may further inform the safety profile index by, forexample, allowing the external processing database 108 to analyze thedimensions of the vehicle prior to a user attempting to obtain theinitial vehicle profile.

To illustrate, if the user is attempting to obtain an initial vehicleprofile for a large bus, the profile safety index should reflect thefact that the time required to obtain the initial vehicle profile (e.g.,capturing video image data of the vehicle 102 exterior) may be greaterthan the time required to obtain an initial vehicle profile of amid-size sedan. Hence, because the time required to obtain the initialvehicle profile will be greater for the bus than for the mid-size sedan,the likelihood of factors based on the geographic location and/orproximate traffic information, as described above, impacting the user intheir attempt may also be increased.

The method continues at block 506 by transmitting a notification fordisplay on a mobile device indicating whether it is safe to obtain aninitial vehicle profile associated with a risk evaluation. Block 506 maybe performed by, for example, the external processing server 108.

In embodiments, the profile safety index indicates whether it is safefor the user to obtain the initial vehicle profile. Accordingly, inthese embodiments, transmitting the notification for display on themobile device indicating whether it is safe to obtain the initialvehicle profile may include comparing the profile safety index to aprofile safety index threshold. The profile safety index threshold maybe a minimum allowable safety index for the user to obtain the initialvehicle profile. For example, if the profile safety index is a numericalscore ranging between 0-100, then the profile safety index threshold maybe 80. Thus, if the external processing server 108 determines that theprofile safety index is equal to 77, the external processing server 108may transmit a notification indicating that it is unsafe for the user toobtain the initial vehicle profile. Additionally or alternatively, theexternal processing server 108 may determine a risk indicator thatindicates the relative risk associated with attempting to obtain aninitial vehicle profile at a certain location. In that instance, if thedetermined risk indicator is less than or equal to a maximum riskindicator threshold, the external processing server 108 may transmit amessage indicating that it is safe to obtain the initial vehicleprofile.

It is to be understood that the initial vehicle profile may indicate afirst set of images intended to establish a profile and/or coveragepolicy corresponding to a risk evaluation, a set of images intended tobegin the claims process for a risk evaluation, or any combinationtherein. For example, the initial vehicle profile may include a set ofimages featuring the vehicle 102 a user may send to a risk evaluatingentity (e.g., to the provider server 106) requesting an initial riskevaluation. In another example, the initial vehicle profile may includea second set of images featuring the vehicle 102 a user may send to therisk evaluating entity requesting an evaluation of damage incurred tothe vehicle 102 against a pre-established baseline. The pre-establishedbaseline may have been previously established by the user and mayinclude a first set of images featuring the vehicle 102 against whichthe second set of images may be compared to facilitate the riskevaluating entity's adjustment to an associated risk evaluation.

The method 500 continues at block 508 by capturing video data indicativeof the vehicle 102. As mentioned herein, the video data may be real-timestreaming data in addition to pre-recorded live video footage indicatingthe vehicle 102. The vehicle 102 may be indicated in the video datawholly, partly, or as is necessary for the risk evaluation. For example,the imaging apparatus 208 may capture the video data indicative of thevehicle 102 as a user walks around the exterior of the vehicle 102 whileholding the user electronic device 104. Block 508 may be performed by,for example, the imaging apparatus 208.

The method 500 continues at block 510 by analyzing the video data toidentify a plurality of profile features. The profile features mayreference the identification information discussed with reference toFIGS. 3A-3R and 4A-4J (e.g., year, make, model, color, and/or VIN ofvehicle 102, etc.). For example, the external processing server 108 mayanalyze the video data by video analysis techniques including objectrecognition (OR), object character recognition (OCR), and other suitablemethods. Block 510 may be performed by, for example, the externalprocessing server 108.

In embodiments, the video data includes profile features indicative ofusers performing personal care activities. For example, the video datamay include profile features indicative of a user taking a walk,running, stretching, weightlifting, swimming, cooking, a user's dietplan, and/or other activities indicative of a healthy, low-risklifestyle. In another example, the video data may include profilefeatures indicative of a user rehabilitating an injury (e.g., purchasingknee braces, wrist splints, etc.), performing physical therapy,providing progress charts corresponding to the injury rehabilitation,and/or other activities indicative of risk-reducing physicalimprovement. Additionally, it is to be understood that such profilefeatures may be applied to various risk evaluations, including but notlimited to, personal life insurance policies, health insurance policies,medical risk evaluations (e.g., surgical risk evaluations, treatmentrisk evaluations), other risk evaluations, and any combination therein.

The method 500 continues at block 512 by determining a first profilefeature from the plurality of profile features. The first profilefeature may be related to the vehicle 102. For example, if a user isattempting to obtain an initial vehicle profile, the first profilefeature may include images of the vehicle taken from each of the variousperspectives discussed with reference to FIGS. 3H-3P (e.g., front,driver side, driver side front, driver side rear, passenger side front,passenger side, passenger side rear, rear, etc.). Block 512 may beperformed by, for example, the external processing server 108.

In embodiments, the user is attempting to obtain claim documents, asdiscussed with reference to FIGS. 4A-4J. Thus, the first profile featuremay include an image of one, some, or all of the various perspectivediscussed with reference to FIGS. 3H-3P. To illustrate, if a user isattempting to obtain claim documents, the user may have only damaged oneportion of the vehicle 102 (e.g., scraped the front bumper, scratchedthe driver's side rear panel, etc.). The external processing server 108may correspondingly determine a first profile feature associated withthe scraped front bumper or the scratched driver's side rear panel.Thus, when the user attempts to obtain an initial vehicle profilecorresponding to a specific risk evaluation event, the externalprocessing server 108 may determine a first profile feature specific tothe risk evaluation event.

The method 500 continues at block 514 by determining a second profilefeature from the plurality of profile features. The second profilefeature may be related to an image verification indicator. As discussedfurther herein in reference to FIGS. 3G and 4E, the system (100, 200)may require authentication for any claim documents or other informationsubmitted as part of a risk evaluation. As such, the risk evaluation mayrequire the second profile feature to be included when capturing thevideo data indicative of the vehicle to perform the authentication, andthus avoid submission issues to increase the overall level of customerservice and satisfaction. Block 514 may be performed by, for example,the external processing server 108.

For example, and in embodiments, the second profile feature includes afacial image of the user. Further in these embodiments, the imageverification indicator includes a known facial image of the user. Thus,in these embodiments, the system (100, 200) attempts to authenticate thevideo image data by extracting identifying information corresponding tothe user. The external processing server 108 may utilize techniquesincluding pattern recognition algorithms, facial recognition algorithms,OR, OCR, or other suitable extraction methods.

It should be understood that both the first profile feature and thesecond profile feature may include one or more of the plurality ofprofile features. As such, and in embodiments, the first profile featureand the second profile feature may be referenced as the “first profilefeatures” and the “second profile features,” respectively.

The method 500 continues at block 516 by comparing the second profilefeature to the image verification indicator. The image verificationindicator may be, for example, a stored image of the user or otherextracted characteristics of the user's face based on similar techniquesdescribed above (e.g., pattern recognition algorithms, facialrecognition algorithms, OR, OCR, etc.). For example, the imageverification indicator may be any other identifiable characteristicconcerning the user, such as a tattoo, birthmark, hair color, or othercharacteristic that can be determined by the external processing server108 or other suitable device using the techniques described above.Additionally or alternatively, the image verification indicator mayinvolve a user including an audial cue (e.g., password, identifyingphrase, etc.) that the external processing server 108 or other suitabledevice will recognize as associated with the user. For example, theserver's (106, 108) database (210, 218) may include a known image orcharacteristics of a user in addition to the phrase/password beingspoken in the user's tone of voice (e.g., an audio recording of the userspeaking the phrase/password).

The method 500 continues at block 518 by generating an imageverification score based on the comparison of the second profile featureto the image verification indicator. The image verification score may bean alphanumerical score or other suitable indication. As mentionedherein, the second profile feature will include similar features as theimage verification indicator, and those similar features will becompared to one another to determine the degree of similarity theyshare. Block 518 may be performed by, for example, the externalprocessing server 108.

In embodiments, generating the image verification score may be based ona comparison of the first profile feature and the second profile featureto the image verification indicator. For example, the image verificationindicator may include details corresponding to both the vehicle 102 andthe user, such that at least a portion of the first profile feature andat least a portion of the second profile feature may be required for acomplete comparison to the image verification indicator. To illustrate,the image verification indicator may include an image of the driver'sside front of the vehicle 102 and an image of the user's face. Thus, togenerate the image verification score, a user would need to capture atleast an image of the driver's side front of the vehicle 102 and theirface for a complete comparison. Accordingly, if a user only captures animage of the driver's side front of the vehicle 102 but does not includean image of the user's face, the external processing server 108 mayreject the submitted video data because a complete comparison to theimage verification indicator could not be performed.

Alternatively, the external processing server 108 may permit incompletecomparisons of the first and second profile features to the imageverification indicator if the resulting image verification score issufficiently high. For example, if the user only captures an image ofthe driver's side front of the vehicle 102 but does not include an imageof the user's face, the external processing server 108 may accept thesubmitted image if the comparison of the first profile feature to thecorresponding component of the image verification indicator (e.g., animage of the driver's side front of the vehicle 102) is sufficientlysimilar. The external processing server 108 may indicate that thecomparison is sufficiently similar if the first profile feature and theimage verification indicator share a threshold number of qualities, eachof the determined qualities of both images are equal to or above asimilarity threshold, or any other suitable metric and/or combinationtherein.

Moreover, the comparison of profile features to the image verificationindicator may include a weighted feature comparison. For example, assumethe image verification indicator includes a plurality of features suchas a driver's front headlight, driver's front fender, driver's frontside mirror, driver's front engine compartment hood, and a damaged hoodornament. Due to the relatively unique quality of the damaged hoodornament, the damaged hood ornament may receive a larger weight than theheadlight, fender, side mirror, and engine compartment hood whencomparing the first profile feature to the image verification indicator.Thus, if the first profile feature includes an identical damaged hoodornament, the external processing server 108 may generate a high imageverification score to reflect the high likelihood that the vehicle 102indicated in the first profile feature represents the same vehicle 102indicated by the image verification indicator.

In embodiments, generating the image verification score based on thecomparison of the second profile feature to the image verificationindicator includes weighting the image verification score based on thegeographical location of the vehicle. For example, and as mentionedpreviously, the video data may include geotagged location data toindicate where the video data was and/or may be obtained. The imageverification indicator may include information relating the historicalgeographical data indicating the typical locations of a vehicle 102and/or user. Thus, when comparing the second profile feature to theimage verification indicator, the external processing server 108 mayinclude the current geotagged location associated with the secondprofile feature to further inform the image verification scoregeneration. To illustrate, if a vehicle 102 is typically located in auser's driveway, then the external processing server 108 may generate ahigh image verification score in response to comparing a second profilefeature associated with a geotagged location in the user's driveway withthe image verification indicator.

Still further in these embodiments, generating the image verificationscore based on the comparison of the second profile feature to the imageverification indicator includes weighting the image verification scorebased on the geographical location of the vehicle. As described above,certain locations associated with typical locations of a vehicle 102and/or a user may influence the external processing server's 108generation of an image verification score. In response to receiving suchtypical location data, the external processing server 108 may assignweighting values to each received location. Accordingly, the moretypical (e.g., frequent) the locations are with respect to the vehicle102 and/or the user, the higher the weighting values may be. Toillustrate, if a vehicle 102 is parked in the user's driveway for amajority of the time indicated by the data received at the externalprocessing server 108, then the external processing server 108 mayassign the user's driveway a correspondingly high weighting value.Similarly, if the vehicle 102 was driving on an obscure highway once inthe observable lifetime of the vehicle 102, then the external processingserver 108 may assign a correspondingly low weighting value to theobscure highway.

The method 500 continues at block 520 by updating the risk evaluation toinclude the initial vehicle profile based on the first profile featureindicating the image verification score relative to an imageverification threshold. For example, the first profile feature mayinclude two or more of the plurality of profile features, and theinitial vehicle profile may include one or more of the first profilefeatures. Correspondingly, the initial vehicle profile may indicate eachof the features related to an risk evaluation event. Block 520 may beperformed by, for example, the provider server 106.

To illustrate, assume the risk evaluation event is a vehicle accident.In this event, the first profile features may include images indicativeof, inter alia, a damaged radiator, a damaged front fender, a damagedengine compartment hood, an undamaged passenger front door, and anundamaged passenger rear door. The initial vehicle profile may includeonly the damaged radiator, the damaged front fender, and the damagedengine compartment hood, to reflect the features of interest, withrespect to the risk evaluation. Accordingly, the image verificationscore may be compared to an image verification threshold, and dependingon the results of the comparison, the initial vehicle profile may beincluded in the risk evaluation (e.g., to facilitate claim processing,medical evaluations/underwriting, mechanic assessments, etc.). Forexample, the comparison of the image verification score to the imageverification threshold may indicate that the image verification score isgreater than the image verification threshold, such that the initialvehicle profile is authenticated, and thus should be included in therisk evaluation. It is to be appreciated that the comparison may requirethe image verification score to satisfy any suitable relationshiprelative to the image verification threshold (e.g., greater than, lessthan, equal to, etc.) for the initial vehicle profile to be included inthe risk evaluation.

As previously stated, the initial vehicle profile may reference a firstset of images intended to establish a risk evaluation profile, policy,and/or other account, a set of images intended to begin the claimsprocess for a risk evaluation, medical evaluation/underwriting, mechanicassessments, etc., or any combination therein. For example, assume therisk evaluation event is a user applying for insurance coverage tocomply with state regulations requiring initial vehicle inspectionsprior to issuing insurance coverage and/or processing insurance claimswith respect to the vehicle. In this event, the first profile featuresmay include images indicative of, inter alia, each of the perspectivesof the vehicle 102 discussed with reference to FIGS. 3H-3P and an imageof the user's face. The initial vehicle profile may include only theperspectives of the vehicle 102, to satisfy the necessary initialvehicle inspection criteria for the relevant state (e.g., Massachusettsmay require more perspective images than Florida). Accordingly, based ona comparison of the image verification score to an image verificationthreshold, the initial vehicle profile may be included in the riskevaluation (e.g., to facilitate insurance acquisition such as insurancedeductible estimation, insurance premium estimation, insurancebenefits/incentives determinations, etc.).

In embodiments, the video data is a first video data, the plurality ofprofile features is a plurality of first profile features, and the imageverification score is a first image verification score. Moreover, themethod 500 may further comprise capturing a second video data indicativeof an insurance-related event; analyzing the second video data toidentify a plurality of second profile features; determining a thirdprofile feature from the plurality of second profile features, whereinthe third profile feature is related to the insurance-related event;determining a fourth profile feature from the plurality of secondprofile features, wherein the fourth profile feature is related to theimage verification indicator; comparing the fourth profile feature tothe image verification indicator; generating a second image verificationscore based on the comparison of the fourth profile feature to the imageverification indicator; and updating an aspect of the risk evaluationbased on the third profile feature indicating the second imageverification score relative to the image verification threshold.

For example, the system (100, 200) may determine that the data includedin the initial vehicle profile is insufficient, and thus requiresfurther information to process the initial vehicle profile for aspecific risk evaluation event. Thus, the provider server 106 maygenerate a notification for display on a user interface of the userelectronic device 104, indicating that further information is required.Afterwards, the imaging apparatus 208 may capture the second video data,and a plurality of features may be determined from the second videodata.

To illustrate, the first video data may not have included a sufficientlyclear image of a damaged area of the vehicle 102 for the provider server106 to include the initial vehicle profile in the risk evaluation. Thus,the provider server 106 may generate a notification instructing the userto capture a second video data including the damaged area in an attemptto create a more illustrative initial vehicle profile corresponding tothe risk evaluation event. If the second video data includes asufficient indication of the damaged area (e.g., the third profilefeature), as determined by one or both of the provider server 106 and/orthe external processing server 108, then one or both of the providerserver 106 and/or the external processing server 108 may modify theinitial vehicle profile to include the indication of the damaged areafrom the second video data.

By providing a system and method that allow obtaining an initial vehicleprofile with image verification analytics as described herein, variousadvantages are achieved. For example, the system and method provideand/or are implemented through the use of a device(s) that provideinformation particularly suited for use with other features of thesystem and method to obtain an initial vehicle profile with imageverification analytics. Notably, the system and method provide aseamless solution to obtaining an initial vehicle profile with imageverification analytics by obtaining and analyzing all necessary datathrough a single video image data capture. Moreover, the system andmethod analyze situational data to provide a video image data capturerecommendation corresponding to an enhanced safety evaluation.Additionally, the system and method robustly validate the authenticityof each submitted video image data capture through additional featureanalytics incorporated in the single video image data capture. Theseadvantageous features collectively facilitate more accurate andexpeditious claim verification/processing. Correspondingly, the moreaccurately and efficiently an evaluating entity (e.g., insurancecompany) can verify and pay claims, the more satisfied customers may bethrough receiving lower rates with a higher level of service. Otheradvantages will be recognized by one of ordinary skill in the art inlight of the teaching and disclosure herein.

As will be apparent from the above description, and as should beappreciated with respect to all examples presented herein, the functionsor operations shown in FIG. 5 may be performed in any suitable order,any desired number of times, and/or with any suitable variation to theparticular order and/or combination shown so as to achieve a desiredresult, such as a desired manner of obtaining an initial vehicle profilewith image verification analytics.

IV. Additional Considerations

The following additional considerations apply to the foregoingdiscussion. Throughout this specification, plural instances mayimplement functions, components, operations, or structures described asa single instance. As noted above, although individual functions andinstructions of one or more methods are illustrated and described asseparate operations, one or more of the individual operations may beperformed concurrently, and nothing requires that the operations beperformed in the order illustrated. Structures and functionalitypresented as separate components in example configurations may beimplemented as a combined structure or component. Similarly, structuresand functionality presented as a single component may be implemented asseparate components. These and other variations, modifications,additions, and improvements fall within the scope of the subject matterherein.

The methods described in this application may include one or morefunctions or routines in the form of non-transitory computer-executableinstructions that are stored in a tangible computer-readable storagemedium and executed using a processor of a computing device (e.g., theuser electronic device 104, the provider server 106, the externalprocessing server 108 and/or any other computing devices within theexample system 100 in any suitable combination). The routines may beincluded as part of any of the modules described in relation to FIG. 1and/or FIG. 2 or as part of a module that is external to the systemillustrated by FIG. 1 and/or FIG. 2. For example, the methods orportions thereof may be part of a browser application(s) or anapplication(s) running on any of the devices in the example system 100as a plug-in or other module of the browser application. Further, themethods may be employed as “software-as-a-service” to provide, forexample, the user electronic device 104, the provider server 106, theexternal processing server 108, and/or any other computing devices withaccess to the example system 100 and/or example system 200.

Additionally, certain aspects are described herein as including logic ora number of functions, components, modules, blocks, or mechanisms.Functions may constitute either software modules (e.g., non-transitorycode stored on a tangible machine-readable storage medium) or hardwaremodules. A hardware module is a tangible unit capable of performingcertain operations and may be configured or arranged in a certainmanner. In example embodiments, one or more computer systems (e.g., astandalone, client or server computer system) or one or more hardwaremodules of a computer system (e.g., a processor or a group ofprocessors) may be configured by software (e.g., an application orapplication portion) as a hardware module that operates to performcertain operations as described herein.

In various embodiments, a hardware module may be implementedmechanically or electronically. For example, a hardware module maycomprise dedicated circuitry or logic that is permanently configured(e.g., as a special-purpose processor, such as a field programmable gatearray (FPGA) or an application-specific integrated circuit (ASIC) toperform certain functions). A hardware module may also compriseprogrammable logic or circuitry (e.g., as encompassed within ageneral-purpose processor or other programmable processor) that istemporarily configured by software to perform certain operations. Itwill be appreciated that the decision to implement a hardware modulemechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the term hardware should be understood to encompass atangible entity, be that an entity that is physically constructed,permanently configured (e.g., hardwired), or temporarily configured(e.g., programmed) to operate in a certain manner or to perform certainoperations described herein. Considering embodiments in which hardwaremodules are temporarily configured (e.g., programmed), each of thehardware modules need not be configured or instantiated at any oneinstance in time. For example, where the hardware modules comprise ageneral-purpose processor configured using software, the general-purposeprocessor may be configured as respective different hardware modules atdifferent times. Software may accordingly configure a processor, forexample, to constitute a particular hardware module at one instance oftime and to constitute a different hardware module at a differentinstance of time.

Hardware and software modules may provide information to, and receiveinformation from, other hardware and/or software modules. Accordingly,the described hardware modules may be regarded as being communicativelycoupled. Where multiple of such hardware or software modules existcontemporaneously, communications may be achieved through signaltransmission (e.g., over appropriate circuits and buses) that connectthe hardware or software modules. In embodiments in which multiplehardware modules or software are configured or instantiated at differenttimes, communications between such hardware or software modules may beachieved, for example, through the storage and retrieval of informationin memory structures to which the multiple hardware or software moduleshave access. For example, one hardware or software module may perform anoperation and store the output of that operation in a memory device towhich it is communicatively coupled. A further hardware or softwaremodule may then, at a later time, access the memory device to retrieveand process the stored output. Hardware and software modules may alsoinitiate communications with input or output devices, and may operate ona resource (e.g., a collection of information).

The various operations of example functions and methods described hereinmay be performed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions. The modulesreferred to herein may, in some example embodiments, compriseprocessor-implemented modules.

Similarly, the methods or functions described herein may be at leastpartially processor-implemented. For example, at least some of thefunctions of a method may be performed by one or processors orprocessor-implemented hardware modules. The performance of certain ofthe functions may be distributed among the one or more processors, notonly residing within a single machine, but deployed across a number ofmachines. In some example embodiments, the processor or processors maybe located in a single location (e.g., within a home environment, anoffice environment or as a server farm), while in other embodiments theprocessors may be distributed across a number of locations.

The one or more processors may also operate to support performance ofthe relevant operations in a “cloud computing” environment or as a“software as a service” (SaaS). For example, at least some of thefunctions may be performed by a group of computers (as examples ofmachines including processors), these operations being accessible via anetwork (e.g., the Internet) and via one or more appropriate interfaces(e.g., application program interfaces (APIs)).

The performance of certain of the operations may be distributed amongthe one or more processors, not only residing within a single machine,but deployed across a number of machines. In some example embodiments,the one or more processors or processor-implemented modules may belocated in a single geographic region (e.g., within a home environment,an office environment, or a server farm). In other example embodiments,the one or more processors or processor-implemented modules may bedistributed across a number of geographic regions.

Still further, the figures depict preferred embodiments of an examplesystem 100 and/or example system 200 and methods for purposes ofillustration only. One of ordinary skill in the art will readilyrecognize from the following discussion that alternative embodiments ofthe structures and methods illustrated herein may be employed withoutdeparting from the principles described herein.

Upon reading this disclosure, those of skill in the art will appreciatestill additional alternative structural and functional designs for asystem and method for obtaining an initial vehicle profile with imageverification analytics. Thus, while particular embodiments andapplications have been illustrated and described, it is to be understoodthat the disclosed embodiments are not limited to the preciseconstruction and components disclosed herein. Various modifications,changes and variations, which will be apparent to those skilled in theart, may be made in the arrangement, operation and details of the methodand apparatus disclosed herein without departing from the spirit andscope defined in the appended claims.

To the extent that any meaning or definition of a term in this documentconflicts with any meaning or definition of the same term in a documentincorporated by reference, the meaning or definition assigned to thatterm in this document shall govern. Although the text sets forth adetailed description of numerous different embodiments, it should beunderstood that the legal scope of the description is defined by thewords of the claims set forth at the end of this patent. The detaileddescription is to be construed as exemplary only and does not describeevery possible embodiment since describing every possible embodimentwould be impractical, if not impossible. Numerous alternativeembodiments could be implemented, using either current technology ortechnology developed after the filing date of this patent, which wouldstill fall within the scope of the claims. While particular embodimentsof the present invention have been illustrated and described, it wouldbe obvious to those skilled in the art that various other changes andmodifications can be made without departing from the spirit and scope ofthe invention. It is therefore intended to cover in the appended claimsall such changes and modifications that are within the scope of thisinvention.

The patent claims at the end of this patent application are not intendedto be construed under 35 U.S.C. § 112(f) unless traditionalmeans-plus-function language is expressly recited, such as “means for”or “step for” language being explicitly recited in such claims. Thesystems and methods described herein are directed to an improvement tocomputer functionality, and improve the functioning of conventionalcomputers.

What is claimed is:
 1. A video analytics based image verification systemfor obtaining initial vehicle profiles, the system comprising: one ormore computing devices configured to: receive a geographic location of avehicle and proximate traffic information, determine a profile safetyindex based on the geographic location and the proximate trafficinformation, transmit a notification for display on a mobile deviceindicating whether it is safe for a user to obtain an initial vehicleprofile associated with a risk evaluation, receive video data indicativeof the vehicle, analyze the video data to identify a plurality ofprofile features, determine a first profile feature from the pluralityof profile features, wherein the first profile feature is related to thevehicle, determine a second profile feature from the plurality ofprofile features, wherein the second profile feature is related to animage verification indicator, determine a comparison of the secondprofile feature to the image verification indicator, generate an imageverification score based on the comparison of the second profile featureto the image verification indicator, generate the initial vehicleprofile based on the first profile feature, and in response to acomparison of the image verification score with an image verificationthreshold, update the risk evaluation to include the initial vehicleprofile.
 2. The video analytics based image verification system of claim1, wherein the geographic location of the vehicle is a real-timeindication of a location of the vehicle; and proximate trafficinformation is indicative of one or more of (i) an amount of expectedtraffic proximate to the vehicle based on the geographic location of thevehicle or (ii) an amount of actual traffic proximate to the vehiclebased on the geographic location of the vehicle.
 3. The video analyticsbased image verification system of claim 2, wherein the one or morecomputing devices are further configured to determine the profile safetyindex based on at least one of (i) a time of day, (ii) a current weathercondition at the geographic location, (iii) an expected weathercondition at the geographic location, (iv) a historical weather patternat the geographic location, (v) a make of the vehicle, or (vi) a modelof the vehicle.
 4. The video analytics based image verification systemof claim 1, wherein the profile safety index indicates whether it issafe for the user to obtain the initial vehicle profile, and the one ormore computing devices are further configured to: compare the profilesafety index to a profile safety index threshold, wherein the profilesafety index threshold is a minimum allowable safety index for the userto obtain the initial vehicle profile.
 5. The video analytics basedimage verification system of claim 1, wherein the second profile featureincludes a facial image of the user, the image verification indicatorincludes a known facial image of the user, and wherein generating theimage verification score based on the comparison of the second profilefeature to the image verification indicator includes weighing the imageverification score based on the geographical location of the vehicle. 6.The video analytics based image verification system of claim 1, whereinthe one or more computing devices are further configured to generate theimage verification score based on a comparison of the first profilefeature and the second profile feature to the image verificationindicator.
 7. The video analytics based image verification system ofclaim 1, wherein the video data is a first video data, the plurality ofprofile features is a plurality of first profile features, the imageverification score is a first image verification score, the one or morecomputing devices are further configured to: receive a second video dataindicative of an insurance-related event, analyze the second video datato identify a plurality of second profile features, determine a thirdprofile feature from the plurality of second profile features, whereinthe third profile feature is related to the insurance-related event,determine a fourth profile feature from the plurality of second profilefeatures, wherein the fourth profile feature is related to the imageverification indicator, compare the fourth profile feature to the imageverification indicator, and generate a second image verification scorebased on the comparison of the fourth profile feature to the imageverification indicator; and update an aspect of the risk evaluationbased on the third profile feature indicating the second imageverification score relative to the image verification threshold.
 8. Avideo analytics based image verification method for obtaining initialvehicle profiles, the method comprising: receiving, by one or morecomputing devices, a geographic location of a vehicle and proximatetraffic information; determining, by the one or more computing devices,a profile safety index based on the geographic location and theproximate traffic information; transmitting, by the one or morecomputing devices, a notification for display on a mobile deviceindicating whether it is safe for a user to obtain an initial vehicleprofile associated with a risk evaluation; capturing, by the one or morecomputing devices, video data indicative of the vehicle; analyzing, bythe one or more computing devices, the video data to identify aplurality of profile features; determining, by the one or more computingdevices, a first profile feature from the plurality of profile features,wherein the first profile feature is related to the vehicle;determining, by the one or more computing devices, a second profilefeature from the plurality of profile features, wherein the secondprofile feature is related to an image verification indicator;determining, by the one or more computing devices, a comparison of thesecond profile feature to the image verification indicator; generating,by the one or more computing devices, an image verification score basedon the comparison of the second profile feature to the imageverification indicator; generating the initial vehicle profile based onthe first profile feature; and in response to a comparison of the imageverification score with an image verification threshold, updating, bythe one or more computing devices, the risk evaluation to include theinitial vehicle profile.
 9. The video analytics based image verificationmethod of claim 8, wherein the geographic location of the vehicle is areal-time indication of a location of the vehicle, and proximate trafficinformation is indicative of one or more of (i) an amount of expectedtraffic proximate to the vehicle based on the geographic location of thevehicle or (ii) an amount of actual traffic proximate to the vehiclebased on the geographic location of the vehicle.
 10. The video analyticsbased image verification method of claim 9, wherein determining theprofile safety index is further based on at least one of (i) a time ofday, (ii) a current weather condition at the geographic location, (iii)an expected weather condition at the geographic location, (iv) ahistorical weather pattern at the geographic location, (v) a make of thevehicle, or (vi) a model of the vehicle.
 11. The video analytics basedimage verification method of claim 8, wherein the profile safety indexindicates whether it is safe for the user to obtain the initial vehicleprofile, transmitting the notification for display on the mobile deviceindicating whether it is safe to obtain the initial vehicle profileincludes comparing the profile safety index to a profile safety indexthreshold, and the profile safety index threshold is a minimum allowablesafety index for the user to obtain the initial vehicle profile.
 12. Thevideo analytics based image verification method of claim 8, wherein thesecond profile feature includes a facial image of the user, the imageverification indicator includes a known facial image of the user, andwherein generating the image verification score based on the comparisonof the second profile feature to the image verification indicatorincludes weighing the image verification score based on the geographicallocation of the vehicle.
 13. The video analytics based imageverification method of claim 8, wherein generating the imageverification score is based on a comparison of the first profile featureand the second profile feature to the image verification indicator. 14.The video analytics based image verification method of claim 8, whereinthe video data is a first video data, the plurality of profile featuresis a plurality of first profile features, and the image verificationscore is a first image verification score, the method furthercomprising: capturing, by the one or more computing devices, a secondvideo data indicative of an insurance-related event; analyzing, by theone or more computing devices, the second video data to identify aplurality of second profile features; determining, by the one or morecomputing devices, a third profile feature from the plurality of secondprofile features, wherein the third profile feature is related to theinsurance-related event; determining, by the one or more computingdevices, a fourth profile feature from the plurality of second profilefeatures, wherein the fourth profile feature is related to the imageverification indicator; comparing, by the one or more computing devices,the fourth profile feature to the image verification indicator;generating, by the one or more computing devices, a second imageverification score based on the comparison of the fourth profile featureto the image verification indicator; and updating, by the one or morecomputing devices, an aspect of the risk evaluation based on the thirdprofile feature indicating the second image verification score relativeto the image verification threshold.
 15. A computer readable storagemedium comprising non-transitory computer readable instructions storedthereon for obtaining initial vehicle profiles with image verificationanalytics, wherein the instructions when executed on one or moreprocessors cause the one or more processors to: receive a geographiclocation of a vehicle and proximate traffic information; determine aprofile safety index based on the geographic location and the proximatetraffic information; transmit a notification for display on a mobiledevice indicating whether it is safe for a user to obtain an initialvehicle profile associated with a risk evaluation; receive video dataindicative of the vehicle; analyze the video data to identify aplurality of profile features; determine a first profile feature fromthe plurality of profile features, wherein the first profile feature isrelated to the vehicle; determine a second profile feature from theplurality of profile features, wherein the second profile feature isrelated to an image verification indicator; determine a comparison ofthe second profile feature to the image verification indicator; generatean image verification score based on the comparison of the secondprofile feature to the image verification indicator; generate theinitial vehicle profile based on the first profile feature; and inresponse to a comparison of the image verification score with an imageverification threshold, update the risk evaluation to include theinitial vehicle profile.
 16. The computer readable storage medium ofclaim 15, wherein the geographic location of the vehicle is a real-timeindication of a location of the vehicle, proximate traffic informationis indicative of one or more of (i) an amount of expected trafficproximate to the vehicle based on the geographic location of the vehicleor (ii) an amount of actual traffic proximate to the vehicle based onthe geographic location of the vehicle, and determining the profilesafety index is further based on at least one of (i) a time of day, (ii)a current weather condition at the geographic location, (iii) anexpected weather condition at the geographic location, (iv) a historicalweather pattern at the geographic location, (v) a make of the vehicle,or (vi) a model of the vehicle.
 17. The computer readable storage mediumof claim 15, wherein the profile safety index indicates whether it issafe for the user to obtain the initial vehicle profile, transmittingthe notification for display on the mobile device indicating whether itis safe to obtain the initial vehicle profile includes comparing theprofile safety index to a profile safety index threshold, and theprofile safety index threshold is a minimum allowable safety index forthe user to obtain the initial vehicle profile.
 18. The computerreadable storage medium of claim 15, wherein the second profile featureincludes a facial image of the user, the image verification indicatorincludes a known facial image of the user, and wherein generating theimage verification score based on the comparison of the second profilefeature to the image verification indicator includes weighing the imageverification score based on the geographical location of the vehicle.19. The computer readable storage medium of claim 15, wherein the videodata is first video data, the plurality of profile features is aplurality of first profile features, the image verification score is afirst image verification score, and wherein the instructions whenexecuted on one or more processors further cause the one or moreprocessors to: receive a second video data indicative of aninsurance-related event; analyze the second video data to identify aplurality of second profile features; determine a third profile featurefrom the plurality of second profile features, wherein the third profilefeature is related to the insurance-related event; determine a fourthprofile feature from the plurality of second profile features, whereinthe fourth profile feature is related to the image verificationindicator; compare the fourth profile feature to the image verificationindicator; generate a second image verification score based on thecomparison of the fourth profile feature to the image verificationindicator; and update an aspect of the risk evaluation based on thethird profile feature indicating the second image verification scorerelative to the image verification threshold.
 20. The computer readablestorage medium of claim 19, wherein an insurance policy is generatedbased on the risk evaluation, and the aspect includes one or more of (i)a cost associated with the insurance policy, (ii) a premium associatedwith the insurance policy, (iii) a deductible associated with theinsurance policy, (iv) a discount associated with the insurance policy,or (v) a coverage level associated with the insurance policy.